基于安全压缩感知的大数据隐私保护

doi:10.11959/j.issn.2096-0271.2020002

Abstract

Abstract:

The current “big bang” of data is mainly driven by interconnection of all things.Various types of IoT sensing devices serving in daily life are constantly capturing personal privacy data.However,these privacy data have become the key targets of network attacks.Data security issues in the resource-constrained IoT applications were analyzed,a novel privacy protection technique based on compressive sensing theory was introduced,which is called secure compressed sensing,and a corresponding big data collection scheme was proposed.As demonstrated by the theoretical and experimental security analysis,there is a conclusive appeal for that secure compressive sensing can be used as a lightweight encryption mechanism which is built into the perception layer to provide first-level security protection for data at almost zero cost.

Key words: secure compressive sensing, big data, Internet of things, privacy protection

CLC Number:

TP309

Ping WANG, Yushu ZHANG, Xing HE, Sheng ZHONG. Big data privacy protection based on secure compressive sensing[J]. Big Data Research, 2020, 6(1): 12-22.

Figures/Tables 6

References 25

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